Distributed storage systems store data within a datastore on memory hardware overlaying one or more memory locations. Watchers may issue standing queries to subscribe to particular pieces of data stored on the distributed system and receive change notifications anytime the subscribing data undergoes a mutation. For instance, a writer may execute write transactions to modify/mutate particular pieces of data stored on the distributed system and watchers subscribing to the data are notified when the data is modified. However, increases in demand on the distributed system, when multiple changes/writes occur simultaneously, result in the distributed system being overrun and unable to stream change notifications in real-time. It is known to drop subscriptions completely to alleviate the load on the distributed system during periods of high demand. For this reason some systems are designed without guarantees of in order delivery and often times ordering is left to the client. However, this results in subscribing watchers receiving inconsistent snapshots of the distributed data. Moreover, it is known to use a change log to record each transaction to the data stored on the distributed system. These change logs record every change made to a datastore, and when a read transaction occurs on the datastore, the change log functions as an on/off check point for all the data for a given snapshot.